Determining In-Depth Information of Mild Cognitive Impairment: Clustering Using Unsupervised Machine Learning

被引：0
|
作者：
Hiransuthikul, Akarin [1 ,2 ]
Chunharas, Chaipat [1 ,2 ]
Thongkam, Achitpol [3 ]
Muadmanee, Wisawin [3 ]
Chotibut, Thiparat [4 ]
Phusuwan, Waragon [2 ]
Petchlorlian, Aisawan
Praditpornsilpa, Kearkiat [5 ]
机构：
[1] Chulalongkorn Univ, Fac Med, Div Neurol, Dept Med, Bangkok, Thailand
[2] Chulalongkorn Univ, Chulalongkorn Cognit Clin & Computat Neurosci, Dept Med, Bangkok, Thailand
[3] Chulalongkorn Univ, Fac Med, Dept Med, Bangkok, Thailand
[4] Chulalongkorn Univ, Fac Med, Dept Med, Div Geriatr Med, Bangkok, Thailand
[5] Chulalongkorn Univ, Dept Med, Fac Med, Div Nephrol, Bangkok, Thailand
来源：
NEUROLOGY | 2021年 / 96卷 / 15期
关键词：
D O I：
暂无
中图分类号：
R74 [神经病学与精神病学];
学科分类号：
摘要：
1352
引用
收藏
页数：3
相关论文
共 50 条
  • [31] Phenotypic clustering of repaired Tetralogy of Fallot using unsupervised machine learning
    Jacquemyn, Xander
    Chinni, Bhargava K.
    Doshi, Ashish N.
    Kutty, Shelby
    Manlhiot, Cedric
    INTERNATIONAL JOURNAL OF CARDIOLOGY CONGENITAL HEART DISEASE, 2024, 17
  • [32] Identification of amnestic mild cognitive impairment by structural and functional MRI using a machine-learning approach
    Hwang, Hyunyoung
    Kim, Si Eun
    Lee, Ho-Joon
    Lee, Dong Ah
    Park, Kang Min
    CLINICAL NEUROLOGY AND NEUROSURGERY, 2024, 238
  • [33] Clustering of Heart Failure Phenotypes in Johannesburg Using Unsupervised Machine Learning
    Mpanya, Dineo
    Celik, Turgay
    Klug, Eric
    Ntsinjana, Hopewell
    APPLIED SCIENCES-BASEL, 2023, 13 (03):
  • [34] Machine Learning Model to Predict Diagnosis of Mild Cognitive Impairment by Using Radiomic and Amyloid Brain PET
    Ciarmiello, Andrea
    Giovannini, Elisabetta
    Pastorino, Sara
    Ferrando, Ornella
    Foppiano, Franca
    Mannironi, Antonio
    Tartaglione, Antonio
    Giovacchini, Giampiero
    CLINICAL NUCLEAR MEDICINE, 2023, 48 (01) : 1 - 7
  • [35] Machine Learning Model To Predict Diagnosis Of Mild Cognitive Impairment By Using Radiomic And Amyloid Brain PET
    Giovacchini, G.
    Giovannini, E.
    Pastorino, S.
    Ferrando, O.
    Mannironi, A.
    Tartaglione, A.
    Ciarmiello, A.
    EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2022, 49 (SUPPL 1) : S103 - S103
  • [36] Classify Parkinson's Disease with Mild Cognitive Impairment: Machine Learning Approach
    Cho, S. S.
    Li, C.
    Koshimori, Y.
    Kim, J.
    Christopher, L.
    Diez-Cirarda, M.
    Valli, M.
    Mihaescu, A.
    Houle, S.
    Strafella, A.
    MOVEMENT DISORDERS, 2019, 34 : S782 - S782
  • [37] Machine learning can predict mild cognitive impairment in Parkinson's disease
    Amboni, Marianna
    Ricciardi, Carlo
    Adamo, Sarah
    Nicolai, Emanuele
    Volzone, Antonio
    Erro, Roberto
    Cuoco, Sofia
    Cesarelli, Giuseppe
    Basso, Luca
    D'Addio, Giovanni
    Salvatore, Marco
    Pace, Leonardo
    Barone, Paolo
    FRONTIERS IN NEUROLOGY, 2022, 13
  • [38] Unsupervised machine learning model to predict cognitive impairment in subcortical ischemic vascular disease
    Qin, Qi
    Qu, Junda
    Yin, Yunsi
    Liang, Ying
    Wang, Yan
    Xie, Bingxin
    Liu, Qingqing
    Wang, Xuan
    Xia, Xinyi
    Wang, Meng
    Zhang, Xu
    Jia, Jianping
    Xing, Yi
    Li, Chunlin
    Tang, Yi
    ALZHEIMERS & DEMENTIA, 2023, 19 (08) : 3327 - 3338
  • [39] PREDICTING MILD COGNITIVE IMPAIRMENT AND DEMENTIA: MACHINE LEARNING VERSUS TRADITIONAL METHODOLOGIES
    Kang, Bada
    Hong, Dahye
    Kim, Jennifer
    Oh, Sarah
    INNOVATION IN AGING, 2024, 8 : 1032 - 1033
  • [40] Machine-Learning Algorithms Based on Screening Tests for Mild Cognitive Impairment
    Park, Jin-Hyuck
    AMERICAN JOURNAL OF ALZHEIMERS DISEASE AND OTHER DEMENTIAS, 2020, 35
12345